Stochastic Dynamic Modeling of Cellular Protein Interactions

Sponsor: NIH/National Institute of General Medical Sciences (NIGMS)

Award Number: R01GM131409

PI: Mark Kon

Co-Is/Co-PIs: Julio Castrillon, Dmitri Beglov, Sandor Vajda

Stochastic methods for modeling molecular-protein interactions form an entirely new set of ap-proaches to the important biological goal of simulating cellular biology in silico. Though great progress has been made in this direction by computational biologists over the past 15 years, the goal of “siliconizing” cellular molecular interactions still remains remote. More precisely, the current level of model realism has led to a plateau in the prediction accuracy of molecular interactions. This motivates the development of some novel dynamic models that incorporate biological dynamic uncertainty, adding a significant layer to the realism of the biological processes. However, such models are computationally daunting, thus motivating the development of efficient and accurate computational methods to solve them.

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